This post will illustrate how to:

- Create a correlation matrix of variables using the
`correlate`

command. - Display a correlation matrix as a covariance matrix.
- Obtain the statistical significance of a correlation using the
`pwcorr`

command.

## Correlation Matrix

We’ll use the **auto** dataset for this tutorial.

```
sysuse auto, clear
```

We’ll create a correlation matrix of four variables — *price*, *mpg*, *weight*, and *length*.

```
correlation price mpg weight length
```

Note: We can shorten the `correlation`

command to `corr`

for convenience.

## Covariance Matrix

If we want to create of covariance matrix, we simply add the `covariance`

option to the `correlation`

command.

```
correlation price mpg weigh length, covariance
```

## Statistical Significance of a Correlation

The `correlation`

command produces a clean correlation matrix (or covariance matrix with the `covariance`

option). If we want to see the statistical significance of a correlation, we need to use the `pwcorr`

command with the `sig`

option.

```
pwcorr price mpg weight length, sig
```